FSuite is a user friendly pipeline consisting in a main perl function, fsuite.pl, that implements the creation of several random sparse submaps on genome-wide data (to remove linkage disequilibrium), in order to run FEstim program.

It needs input files in PLINK format.

As described in this flowchart, FSuite is based on 6 functions corresponding to the following steps:

I have the following error message when using step 3 of FSuite pipeline:

Error in Conditional_proba: qstar[…][1]=0, division by zero
Problem in Conditional_proba in main.

What should I do?

This error message mainly appears when the map/bim file does not have genetic positions (3rd column always equals to 0).

The best way to add the genetic position in your PLINK files is to use –cm-map option of plink2. For human, we recommend using SHAPEIT genetic map.

When genetic map is added to your map/bim file, you need to re-run –create-submaps to generate accurate submaps.

Note that an error message should appears from version 1.0.4 when creating submaps with no genetic positions in the map/bim file.

2. Does FSuite read vcf file?

FSuite does not read vcf file, as this format does not integrate information on the family structure and the genetic positions. Some formatting is thus necessary to convert your vcf file into PLINK files. All these steps can be handle with plink2.

Step 1: Converting your vcf file into PLINK files

plink2 --vcf myfile.vcf --make-bed --out myfile_temp

Note that we recommend using FSuite only on common polymorphisms (MAF >=5%) and that an additional filter can be used at this step with PLINK –maf option (if you have a large dataset to estimate allele frequencies) or with PLINK –extract option (if you have a list of common SNPs with corresponding allele frequencies estimated in a reference sample).

Step 2 (if necessary): Update your fam file if you have families and you need to run FSuite step 4 with –familywise option

3. How can I analyze my whole exome sequencing (WES) data with FSuite?

Analyzing WES data with FSuite requires the same formatting steps as described in FAQ 2, to convert the initial vcf containing all your samples to the final PLINK files.

If you have a small sample size we recommend using our set of common polymorphisms present in WES data (download here], with corresponding PLINK .frq files estimating frequencies in African, European, East-Asian and South-Asian 1000 Genomes phase 3 populations).